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Wagon coupler joist breaking detection method

A railway wagon and detection method technology, which is applied in the field of railway wagon safety, can solve problems such as low reliability, and achieve the effects of ensuring reliability, high accuracy of results, and improving efficiency and accuracy

Inactive Publication Date: 2020-04-28
HARBIN KEJIA GENERAL MECHANICAL & ELECTRICAL CO LTD
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Problems solved by technology

[0004] Aiming at the problem that the breakage of the coupler joist of the existing railway freight car is manually detected and the reliability is low, the present invention provides a method for detecting the breakage of the coupler joist of the railway freight car

Method used

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  • Wagon coupler joist breaking detection method
  • Wagon coupler joist breaking detection method
  • Wagon coupler joist breaking detection method

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specific Embodiment approach 1

[0024] Specific implementation mode 1. Combination Figure 1 to Figure 3 As shown, the present invention provides a method for detecting the breakage of a railway wagon coupler joist, comprising the following steps:

[0025] Step 1: Establish a data set for training, mark the fault area or suspected fault area of ​​the coupler joist fault sample in the data set, and mark the recognition frame by block, and configure a category label for each recognition frame, and the category label includes the fault class label and interference labels;

[0026] Step 2: Build a Faster-Rcnn model based on the ResNet detection model. The Faster-Rcnn model uses a convolutional layer, an activation function, and a pooling layer to extract the feature map of the input coupler joist fault sample; The convolution calculation generates a detection suggestion box; the area pooling layer extracts the suggestion feature from the detection suggestion box; the suggestion feature is sent to the fully conn...

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Abstract

The invention discloses a wagon coupler joist breaking detection method, and belongs to the technical field of wagon safety. The invention aims to solve the problem of low reliability caused by manualdetection of the breaking fault of the coupler joist of the existing rail wagon. The method comprises the steps: establishing a data set for training, marking identification boxes in fault areas or suspected fault areas of coupler joist fault samples in the data set in a blocking mode, and configuring category labels for all the identification boxes; building a Faster-Rcnn model based on a ResNetdetection model, and performing training to obtain a weight coefficient of classification; inputting an image to be identified into the Faster-Rcnn model loaded with the weight coefficient; and carrying out fault category prediction, firstly obtaining a fault initial judgment region in the fault prediction process of the to-be-identified image, then obtaining confidence corresponding to the faultinitial judgment region, determining the fault initial judgment region with the confidence greater than a preset threshold as a fault region, and carrying out alarming. The method is used for detecting the fracture of the coupler joist.

Description

technical field [0001] The invention relates to a method for detecting the breakage of a coupler joist of a railway freight car, and belongs to the technical field of railway freight car safety. Background technique [0002] During the operation of railway freight cars, if the coupler joist is broken, it is very easy to cause a safety accident. Therefore, it is necessary to detect the running state of the coupler joist. At present, the way to check the breakage of the coupler joist is that the inspector judges the collected coupler joist image to determine whether it is broken. Due to high labor costs and low efficiency, and manual methods may cause missed or false detections of faults due to various subjective factors, it is difficult to ensure the safe driving of trucks. [0003] Therefore, in view of the above deficiencies, it is necessary to provide a method for automatic detection of coupler joist faults, using machine learning and deep learning technology, using the ...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06N3/04G06N3/08G01N21/88
CPCG06N3/084G01N21/8851G01N2021/8887G06N3/047G06N3/045G06F18/241G06F18/2415
Inventor 张庆宇
Owner HARBIN KEJIA GENERAL MECHANICAL & ELECTRICAL CO LTD
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